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This reference book compiles the recent advances in computational and experimental modelling to screen and manage Alzheimer’s disease. It covers basic etiopathology and various in vitro and in vivo strategies of disease intervention. The book discusses how computer-aided drug design approaches reduce costs and increase biological test efficiency. It reviews the screening for anti-Alzheimer drugs and biomarker analysis of disease inhibitors. The book also explores mechanistic aspects of neurodegeneration and the use of natural products as therapeutics for Alzheimer’s disease. Key features: Elaborates on the computational modelling of protein target inhibitors as anti-Alzheimer’s agents Explains the role of phytomolecules and natural products in Alzheimer’s therapy Reviews preclinical ways to assess drugs focusing on Alzheimer’s disease Covers biomarker analysis for Alzheimer’s disease Discusses the onset and progression of Alzheimer’s disease The book is meant for professionals, researchers, and students of neuroscience, psychology, and computational neurosciences.
As the largest generation in U.S. history - the population born in the two decades immediately following World War II - enters the age of risk for cognitive impairment, growing numbers of people will experience dementia (including Alzheimer's disease and related dementias). By one estimate, nearly 14 million people in the United States will be living with dementia by 2060. Like other hardships, the experience of living with dementia can bring unexpected moments of intimacy, growth, and compassion, but these diseases also affect people's capacity to work and carry out other activities and alter their relationships with loved ones, friends, and coworkers. Those who live with and care for individuals experiencing these diseases face challenges that include physical and emotional stress, difficult changes and losses in their relationships with life partners, loss of income, and interrupted connections to other activities and friends. From a societal perspective, these diseases place substantial demands on communities and on the institutions and government entities that support people living with dementia and their families, including the health care system, the providers of direct care, and others. Nevertheless, research in the social and behavioral sciences points to possibilities for preventing or slowing the development of dementia and for substantially reducing its social and economic impacts. At the request of the National Institute on Aging of the U.S. Department of Health and Human Services, Reducing the Impact of Dementia in America assesses the contributions of research in the social and behavioral sciences and identifies a research agenda for the coming decade. This report offers a blueprint for the next decade of behavioral and social science research to reduce the negative impact of dementia for America's diverse population. Reducing the Impact of Dementia in America calls for research that addresses the causes and solutions for disparities in both developing dementia and receiving adequate treatment and support. It calls for research that sets goals meaningful not just for scientists but for people living with dementia and those who support them as well. By 2030, an estimated 8.5 million Americans will have Alzheimer's disease and many more will have other forms of dementia. Through identifying priorities social and behavioral science research and recommending ways in which they can be pursued in a coordinated fashion, Reducing the Impact of Dementia in America will help produce research that improves the lives of all those affected by dementia.
This book constitutes the refereed joint proceedings of the 4th International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2020, and the First International Workshop on Topological Data Analysis and Its Applications for Medical Data, TDA4MedicalData 2021, held on September 27, 2021, in conjunction with the 24th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2021. The 7 full papers presented at iMIMIC 2021 and 5 full papers held at TDA4MedicalData 2021 were carefully reviewed and selected from 12 submissions each. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention. TDA4MedicalData is focusing on using TDA techniques to enhance the performance, generalizability, efficiency, and explainability of the current methods applied to medical data.
Alzheimer’s disease is an increasingly common form of dementia and despite rising interest in discovery of novel treatments and investigation into aetiology, there are no currently approved treatments that directly tackle the causes of the condition. Due to its multifactorial pathogenesis, current treatments are directed against symptoms and even precise diagnosis remains difficult as the majority of cases are diagnosed symptomatically and usually confirmed only by autopsy. Alzheimer’s Disease: Recent Findings in Pathophysiology, Diagnostic and Therapeutic Modalities provides a comprehensive overview from aetiology and neurochemistry to diagnosis, evaluation and management of Alzheimer's disease, and latest therapeutic approaches. Intended to provide an introduction to all aspects of the disease and latest developments, this book is ideal for students, postgraduates and researchers in neurochemistry, neurological drug discovery and Alzheimer’s disease.
This book presents essential studies and cutting-edge research results on tau, which is attracting increasing interest as a target for the treatment of Alzheimer's disease. Tau is well known as a microtubule-associated protein that is predominantly localized in the axons of neurons. In various forms of brain disease, neuronal loss occurs, with deposition of hyperphosphorylated tau in the remaining neurons. Important questions remain regarding the way in which tau forms hyperphosphorylated and fibrillar deposits in neurons, and whether tau aggregation represents the toxic pathway leading to neuronal death. With the help of new technologies, researchers are now solving these long-standing questions. In this book, readers will find the latest expert knowledge on all aspects of tau biology, including the structure and role of the tau molecule, tau localization and function, the pathology, drivers, and markers of tauopathies, tau aggregation, and treatments targeting tau. Tau Biology will be an invaluable source of information and fresh ideas for those involved in the development of more effective therapies and for all who seek a better understanding of the biology of the aging brain.
This reference book compiles the recent advances in computational and experimental modeling to screen and manage Alzheimer's disease. The book discusses how computer-aided drug design approaches reduce costs and increase biological test efficiency.
Electroencephalograms (EEGs) are becoming increasingly important measurements of brain activity and they have great potential for the diagnosis and treatment of mental and brain diseases and abnormalities. With appropriate interpretation methods they are emerging as a key methodology to satisfy the increasing global demand for more affordable and effective clinical and healthcare services. Developing and understanding advanced signal processing techniques for the analysis of EEG signals is crucial in the area of biomedical research. This book focuses on these techniques, providing expansive coverage of algorithms and tools from the field of digital signal processing. It discusses their applications to medical data, using graphs and topographic images to show simulation results that assess the efficacy of the methods. Additionally, expect to find: explanations of the significance of EEG signal analysis and processing (with examples) and a useful theoretical and mathematical background for the analysis and processing of EEG signals; an exploration of normal and abnormal EEGs, neurological symptoms and diagnostic information, and representations of the EEGs; reviews of theoretical approaches in EEG modelling, such as restoration, enhancement, segmentation, and the removal of different internal and external artefacts from the EEG and ERP (event-related potential) signals; coverage of major abnormalities such as seizure, and mental illnesses such as dementia, schizophrenia, and Alzheimer’s disease, together with their mathematical interpretations from the EEG and ERP signals and sleep phenomenon; descriptions of nonlinear and adaptive digital signal processing techniques for abnormality detection, source localization and brain-computer interfacing using multi-channel EEG data with emphasis on non-invasive techniques, together with future topics for research in the area of EEG signal processing. The information within EEG Signal Processing has the potential to enhance the clinically-related information within EEG signals, thereby aiding physicians and ultimately providing more cost effective, efficient diagnostic tools. It will be beneficial to psychiatrists, neurophysiologists, engineers, and students or researchers in neurosciences. Undergraduate and postgraduate biomedical engineering students and postgraduate epileptology students will also find it a helpful reference.
A First Course in Systems Biology is an introduction for advanced undergraduate and graduate students to the growing field of systems biology. Its main focus is the development of computational models and their applications to diverse biological systems. The book begins with the fundamentals of modeling, then reviews features of the molecular inventories that bring biological systems to life and discusses case studies that represent some of the frontiers in systems biology and synthetic biology. In this way, it provides the reader with a comprehensive background and access to methods for executing standard systems biology tasks, understanding the modern literature, and launching into specialized courses or projects that address biological questions using theoretical and computational means. New topics in this edition include: default modules for model design, limit cycles and chaos, parameter estimation in Excel, model representations of gene regulation through transcription factors, derivation of the Michaelis-Menten rate law from the original conceptual model, different types of inhibition, hysteresis, a model of differentiation, system adaptation to persistent signals, nonlinear nullclines, PBPK models, and elementary modes. The format is a combination of instructional text and references to primary literature, complemented by sets of small-scale exercises that enable hands-on experience, and large-scale, often open-ended questions for further reflection.
Given the success of Volume I of this Research Topic, we are pleased to announce the launch of Volume II: “The Alzheimer's Disease Challenge”. The repeated failure of clinical trials on the amyloid-based medications and the pessimistic calculations of Alzheimer's disease cost burden for the next few decades present a severe challenge to humankind with severe social implications. In recent years, several alternative diagnostic and treatment procedures have been presented to treat and manage Alzheimer’s disease as it has been nearly impossible to suggest a holistic solution. Several revelations in human biology have highlighted the multiparametric character of the disease. Besides the amyloid aggregation and neurofibrillary tangles that result in Aβ toxicity and tau phosphorylation, processes such as Gene Mutations, Proteins Misfolding, Brain Biochemical and Histopathological Changes, Behavioral Changes, Nutrition and Metabolism Alterations, and Autonomic Dysfunctions due to Central Nervous System dysregulations are common signs and probably early diagnostic biomarkers in most of the Alzheimer's classification categories.
This up-to-date, superbly illustrated book is a practical guide to the effective use of neuroimaging in the patient with cognitive decline. It sets out the key clinical and imaging features of the various causes of dementia and directs the reader from clinical presentation to neuroimaging and on to an accurate diagnosis whenever possible. After an introductory chapter on the clinical background, the available "toolbox" of structural and functional neuroimaging techniques is reviewed in detail, including CT, MRI and advanced MR techniques, SPECT and PET, and image analysis methods. The imaging findings in normal ageing are then discussed, followed by a series of chapters that carefully present and analyze the key findings in patients with dementias. Throughout, a practical approach is adopted, geared specifically to the needs of clinicians (neurologists, radiologists, psychiatrists, geriatricians) working in the field of dementia, for whom this book will prove an invaluable resource.